The instrumented 120mm-APO
Refractor.
Links: =
b>Amateur Astronomy, Personal Pages of Astronomers<=
/a>, Astronomy-links=
a>
=
span>
The
main optical instrument at the "Kolkert-Ob=
servatory"
is an instrumented "go to"-apochromatic
refractor. The following pictures give a good impression of the telesc=
ope
in its present state.
I. General/Original.
The
original outfit of the 120mm Synta-achromate OTA
consists of a Fraunhofer doublet objective moun=
ted in
an adjustable lens cell being part of a baffled aluminium tube. The 2"
focuser is of the rack-and pinion type and contains an aluminium draw-tube.
This OTA is mounted on the CG-4 equatorial mount of my other refractor, the
C102-HD.
Two
standard eyepieces are available, a 7.6 mm Plössl=
,
series 3000 of Meade and a 20 mm one of Celestron. A Celestron polar axis finder scope with cross wire
illumination is available, too. The visual finder telescope is a 6x30 Celestron type with cross wire.=
The
focal length of the 120 mm achromat is standard=
1000
mm ( F/8.3), the light gathering power is 293, t=
he
max. magnitude at which objects can be observed =
is
13.1 and the optical resolution (Dawes limit) is 0.96" (arc).
II. Astrophotography.
Images
of sky-objects are photographed with a PC-controlled, 1-stage cooled
(-30°C) CCD-astrocamera, the 12 bits Starli=
ght-Xpress MX5-C, which makes it possible to record
repetitively single-shot multi-colour pictures. Monitoring and control is
performed with the program STAR2000/MX5-C and/or ASTROART2.0 with the MX5-C
plug-in. Raw images of exposures are colour-converted to LRGB images and
processed with ASTROART, too.
III.
Optical aids and Sky-data.
Optical
options have been extended by replacing the 6x30 finder scope with a 9x50 o=
ne
and fitting a 0.1 lux CCD-=
videocamera
at prime focus to it. This greatly enhances finding and focusing objects up=
to
Magnitude 7. The 0.33 inch B/W sensor of the 12V camera has 725(H)x528(V)
pixels, gives 380 TV lines in horizontal and 450 lines in vertical directio=
n,
has an automatic iris and shutter speed (1/50 to 1/32000), has a 2:1 interl=
ace
scanning system and a S/N ratio better than 50dB.
The
real-time image of this combination is depicted on a TV-monitor on which sc=
reen
a centering cross has been drawn. The circular =
FOV of
this combination is 2.4° and is, together with the square FOV of the
single-shot CCD-astrocamera projected at the Ea=
rth Centered Universe(ECU)-scr=
een,
showing the relevant part of the sky. The centers of
both FOV's are made to coincide at the center cross of the TV monitor and the center
of the CCD-chip of the astrocamera. This simpli=
fies
finding and centering sky-objects to a great ex=
tent.
General information on sky-objects is retrieved from the well-documented
REDSHIFT-3 code.
Further
on a telecompressor lens (Meade 0.63x), a Televue Powermate 5x Barl=
ow and a
12 mm Kellner eyepiece with illuminated double =
cross
wire, mounted in a Flip Mirror Finder (True Technologies) equipped with an =
IR-filter,
have been added. For testing optimized visual focusing and determination of
spherical aberration of the optical train, a dummy eyepiece with a 7 lines =
per
mm Ronchi grating is available. Maximum F-numbe=
r to
be obtained with the Televue Powermate
is F/41.6 at a focal length of 5000 mm.
IV.
Modifications.
A.
Electromechanical.
The
CG-4 mount, of which the bearings and drives have been re-adjusted to
satisfaction, has been upgraded with:
1. an autonomous controlled stepper motor for the right
ascension axis (RA), max. 8x sidereal speed, and
2. a variable speed DC declination motor (JIM's
Mobile)=
to
set/control the declination.
The OTA
focusing device has been equipped with a variable speed DC focusing motor (=
JIM's Mo=
bile)
to focus the image plane and a digital focus read-out (DFRO) to determine i=
ts
position.
The
slew rates of the motorized mount are modest(2&d=
eg;/minute
max.), but suffice at the moment. Slewing to an object chosen in the real t=
ime
planetarium and telescope control program ECU, gives the following pointing
accuracy: s RA=3D ± 3s and s DEC=3D ± 49"(a=
rc).
The
backlash in the two drives of the mount for RA- and DEC rotation at reversa=
l is
6.6s and 51"(arc), respectively. Hysteresis is
well within these values.
The rack-and-pinion
focuser has been exchanged with a dual speed (1:10) Crayford one from Willi=
ams
Optics. It has been adapted for motorized drive and digital position read-o=
ut.
Focusing
on an object is done automatically with the motorized Crayford device. The =
resolution
of the DFRO ( see below), and so the accuracy to
determine the focus plane with this setup is 0.87°rotation of=
the
axis of the focuser, which equals 0.059 mm axial displacement. At a 1/4 l defocusing aberration, =
the
depth of focus is allowed to be within +1/8 and -1/8l. Then, delta-focus runs=
from
0.0597 mm for F/8.3 at l =3D0.43µm to 2.284 mm for F/42 at l =3D0.66µm, respec=
tively.
So, for the F/42-set-up and a resolution of ± 0.059 mm axial
displacement for one count of the DFRO (see below), the defocusing aberrati=
on
should be better than 1/64 l ! =
All
accessories to be used at the focuser draw-tube end are fitted with three
setting screws to facilitate alignment of the optical train, for which a Cheshire eyepiece =
and a
TL-light source are used.
B. Optical conversion =
from achromate to apochromate;=
the
CHROMACORR.
A newly
developed item which is a leap-ahead in the reduction of the secondary spec=
trum
and spherical aberration, i.e. the 150mm achro-apo
converter or Chromacorr, developed at ARIES Ins=
truments,
is also installed. This three-lens system has an over-correction in spheric=
al
aberration of +1/7λ and was ch=
osen as
the doublet objective of the 120 mm shows an under-correction of about
–1/7λ<=
b>. It is the
Chromacorr-O1 and it is threaded in the forward-end of a 2-inch outer diame=
ter
extension tube with such a length that the distance in between the focal st=
op
of an ocular or Barlow and the thread of the Chromacor=
r
can be set from 190 mm up to 225 mm. This assembly is now centered
in the draw-tube with the help of a compression ring. The Chromacorr
extension tube centered in the draw-tube of the
Crayford focuser and the 9x50 finder scope is shown below.

Both
for the original set-up and for the optical train extended with the Chromacorr, results of star-testing, Ronchi-testing
and secondary spectrum determination up to F/42 are reported here.
First
results of star images are also presented here. For the white star Altair,
images (3 sec. exposure) were made at F/8.3 up to F/42 with and without the
Chromacorr-O1 installed. Optimal collimation is mandatory in these
test and asks for some praxis.
V. Automatization.
A.
Digital Setting Circles and Focus Read-Out. =
The
motorized items are connected to digital setting circles (DSC's) and to a d=
igital
focus read out (DFRO) for which encoders have been connected directly to the
different rotation axes of the equatorial mount and to the focusing device.
These systems are home-made. Digitizing of the different encoder signals oc=
curs
with the PCB of a modified PS2-mouse-now called the "Astro-mouse"-and
are converted into discrete counts with the soft=
ware
program "encoder" which runs on an old 364 PC. With a laplink, that PC is connected to the main PC which ru=
ns the
real time planetarium and telescope control program Earth Centered
Universe (ECU). The counts of the DSC's are transformed into RA-and DEC-val=
ues
which are presented both as a (moving) cursor and a numerical window on the
PC/ECU-screen which depicts the area of the sky the telescope is pointing a=
t.
The position of the focus plane is read-out on the 364 PC as integers with a
respective sign for inter- and intra-focus.

B. Telescope
control.=
p>
1. RA-
and DEC-motion.
Actuation
of both the DC DEC-motor and RA-stepper motor is being executed via the
STAR2000 interface module in combination with the accompanying Relay Box. T=
he
speed of the DEC-motor can be continuously controlled manually, while their=
are
next to sidereal rate, two(2) speed options for =
the
RA-motor; 2x and 8x sidereal speed in both East- and West-direction. The lo=
wer
speeds are used for self-guiding and tracking of a chosen celestial object =
in
the FOV of the telescope, while the higher speeds are used for slewing
purposes.
The
STAR2000 interface module from Starlight-Xpress=
is
operated by either the STAR2000 software (telescope control panel) of the M=
X5-C
astrocamera or by the telescope control window =
(move
panel) of ASTROART2.0.
Finding
an object, slewing to an object and centering i=
t is performed by combining the telescope control panel =
window
with the real-time local sky-chart of ECU. Choosing an object in ECU gives =
its
co-ordinates and deviation of the present position the telescope is pointing
at. The latter information is coming from the DSC’s on the equatorial
mount and their "Astro-mouse" interfa=
ce
with ECU. By activating the relevant buttons in the control/move panel, the
deviations are zeroed and the chosen object arrives near or at the optical =
axis
of the telescope as observed in the continuously updated image field of the=
astrocamera MX5-C. For the latter situation
, the camera operates in the focus-mode under ASTROART2.0. At that
moment the position of the optical axis of the telescope and the position of
the chosen object are synchronized and centered=
in
ECU.
-
-
--
2.
Focusing.
Focusing
is performed with the motorized Crayford focuser and the DFRO. The focus-mo=
tor
is actuated via the North- and South-buttons of the move-panel of the teles=
cope
control window in STAR2000 and the result is real-time observed in the
regularly updated image field of the "focus"-window in ASTROART2.=
0.
--
--
VI.
Numerical values of the set-up.
A. FOV (Field of V=
iew).
The
calculated FOV of the ICX 055CK chip of the Starlight Express CCD-camera wi=
th
chip-dimensions of 4.9(horizontal) x 3.6(vertical) mm is for different
F-numbers:
1. F/5,3 (0.63 telecompressor),<=
span
style=3D'color:yellow'>--- -f=3D 630 mm-------26.8' x 19.=
7' (arc)
2.
F/8.3 (standard),--=
-----------------=
span> -f=3D 1000 m=
m-----16.9' x 12.4' (arc)
3.
F/16.6 (one Barlow, 2x),--=
-------- f=3D 2000 mm---=
--- 8.4'
x 6.2' (arc)
4.
F/33.2 (two Barlow's, each 2x),--f=3D 4=
000 mm--- ---4.2' x 3.1' (arc)
5.
F/41.6 (Televue Powermate<=
/span>
5x), f=3D 5000 mm-------3.4' x 2.5' (ar=
c)
For
instance for Jupiter, this leads to a 32% PC-screen occupancy at F/42.
For the
sky-occupancy per pixel in the vertical direction of the chip of this camer=
a,
which has 145.000 pixels (500 hor. x 290 vert.), the following values are obtained:=
1.
F/5.3----------- -4.1"(arc)
2.
F/8.3---------- --2.6"(arc)
3.
F/16.6-----------1.3"(arc)
4.
F/33.2-----------0.6"(arc)
5.
F/41.6 ----------0.5"(arc)
B. Optical Resolut=
ion.
The power
to resolve individual point sources at optical wavelengths from each other =
for
this optical system in combination with the camera mentioned, has been dedu=
ced,
too. The dimensions of the pixels are 9.8 x 12.6 mm. For the average pixel=
size
of 11.2 m=
m and at the
maximum response wavelength (l =3D 0.56 mm) of the chip, the resolution per pixel at the
different F-values is;
1. resolution per pixel at F/8.3 -----------=
-2.31" =
(arc)
2. resolution per pixel at F/16.6-----------=
1.15" =
(arc)
3. resolution per pixel at F/33.2-----------=
0.58" =
(arc)
4. resolution per pixel at F/41.6----------
0.46" (arc)
The
value under 4 is the so-called Nyquist-criterio=
n for
correctly sampling the image of the observed object, for which the Airy-disk
diameter is 0.56 x F-value (in mm). Then good results are obtained with
image-processing.
As it
appears from experimentation, the chromatic aberration at F/42 is negligible
(secondary spectrum is about 0.00006 times the focal length f). =
The
optimal F-number for observing planets for this system is F/40 and for deep=
-sky
objects it is F/20. The magnification at F/42 as seen on my PC-screen, is 790x.
top of page<=
span
lang=3DEN-GB style=3D'mso-ansi-language:EN-GB'>
STAR-TESTING of the modified 1=
20 mm
APO-refractor.
I. Without the Chromacorr installed.
A. Diffract=
ion
patterns for Altair at full aperture.







=
span>
inside focus---------------=
--------------------------------------------focus----------------------------------------------------=
--------outside
focus
These
results of diffraction rings for the white star Altair (magnitude +0.79) of=
the
120 mm doublet objective (f=3D1000 mm) of the Synta
refractor (as bought) were obtained with the Starlight MX-5C astrocamera equipped with an IR-filter. The magnifica=
tion was
about 158 x.
B. Summary of resu=
lts.
-The
secondary spectrum (i.e. difference in focus position D f between yellowish and
purple image) at F/8.3 is .62 mm; so D f/f ≈=
0.00062 fo=
r this
optical system. Quality-Fraunhofer achromatic
doublets have a corresponding value of about 0.0005. =
-Comparing
diffraction patterns with results of simulations (Aberration code) leads to=
the
conclusion that the spherical aberration of the doublet objective without <=
span
class=3DSpellE>Chromacorr is –0.14 l .<=
span
lang=3DEN-GB style=3D'font-size:10.0pt;mso-ansi-language:EN-GB'>=
-Some
astigmatism and an S-zone at 30%-radius is present.=
p>
-Ronchi-testing showed straight, sharp and parallel li=
nes
and so is to unsensitive for deducing aberratio=
ns in
this case.
II. With the Chromacorr
O-1 installed.
A. Diffraction patterns for Altair.
1. Stopped-down=
aperture.







After
collimating the two elements of the objective with the optical axis of the
OTA-tube with the help of the adjustable lens cell and the Cheshire eyepiece, the optical train
involving the Chromacorr O-1 and the doublet
objective was aligned.
These
are the diffraction rings for Altair, obtained from star-testing with the
modified 120 mm Synta doublet refractor stopped=
-down
to a 50 mm aperture and equipped with the Chromacorr-O1 plus self-centering draw-tube adapter. The images were recorded=
with
the MX-5C astrocamera plus IR-filter. The atmos=
phere
was rather steady during these tests.
-Summary of result=
s.
-
Astigmatism has been removed by loosening the retaining ring pressing the
rubber O-ring onto the doublet objective in its cell.
-The
secondary spectrum Δf was improv=
ed to
less than 0.059 mm (the resolution of the Digital Focus Read-Out, DFRO) and=
the
spherical undercorrection was estimated to be l=
ess
than 1/42=
l. Both para=
meters
have been improved substantially by using the Chromacorr-O1! The magnificat=
ion
was 158x.
-It is
noticed that Δf/f=3D0.000=
059,
indicating that this 120mm OTA plus Chromacorr =
O-1
behaves as an excellent apochromate!=
-In the
stopped-down mode, not much can be seen of the S-zone. So it's
amplitude must be smaller than 1/8λ.
-Ronchi-testing showed sharp, straight and parallel li=
nes
all over the field of view.
2. Full =
aperture.









Besides
aperture stopped-down testing, star-testing was also performed with the full
aperture of the Synta 120 mm refractor equipped=
with
the Chromacorr O-1.
The images
above show the diffraction rings for Altair as recorded with the MX-5C astrocamera.
The
effects of the S-zone are still visible. Its effect on images of planets wi=
ll
determine how severe this zoning is. Again
the magnification was abou=
t
158x.
B. Another star.









These
are the diffraction rings for a magnitude +2 light-yellow star of the 120 m=
m Synta doublet refractor equipped with the Chromacorr-=
O1.
The images were recorded with the MX-5C astrocamera.
The atmosphere was rather steady and the magnification was about 158x.
&n=
bsp;
C. Effect of Vixen=
Deluxe
Barlow-lenses on optical performance in star-testing.










<=
/span>
These are
the diffraction rings for Altair of the 120 mm Synta=
span>
doublet refractor plus Chromacorr-O1 and two Vixen Deluxe Barlow’s (t=
wo
times each) as recorded with the MX-5C astrocamera.
The Chromacorr was not optimally aligned, i.e. =
there
is a little lateral red-blue shift.
A minor
effect of the S-zone can be seen in these images while some optical pinchin=
g of
to tightly-fastened set-screws of the Barlow-lenses can be seen, too.<=
/o:p>
The
magnification is 632x.
=
D. The effect of a=
Televue Powermate 5x Barl=
ow on
optical performance.







These are the diff=
raction
rings for Rigel, a magnitude 0.18 blue star, of the 120 mm Synta =
doublet
refractor stopped-down to 50 mm. The telescope was equipped with the
Chromacorr-O1 and the Televue powermate
5x. The images were taken with the MX5-C astrocamera including an IR-filter.=
The atmosphere was=
rather
steady and the magnification was 790x.
The magnitude of t=
he
S-zone (smaller than 1/8λ) is too small to be of importance for image degradation as can be s=
een
in the image of Saturnus(see under III).
III. Saturnus and Jupiter.

=
span>
These multi-shot c=
omposed
pictures were taken with the 120 mm Synta doubl=
et
refractor, equipped with the Chromacorr-O1 and the Tel=
evue
powermate 5x. The
magnification was 790x, while the outdoor temper=
ature
was -5° C.
IV<=
span
style=3D'font-size:13.5pt'>. Mars.

This colour-conver=
ted
single-shot picture was taken at 23.46 hour on 4 September 2003 with the MX=
5-C
camera. The 120 mm Synta doublet refractor was
equipped with theChromacorr-O1 and Televue Powermate 5x.=
span>
=
top of page<=
span
style=3D'font-size:10.0pt;mso-ansi-language:EN-GB'>
=
Back =
home
&n=
bsp;
This CCD
Astrophotography site is owned by =
W.J. Kolkert
[ Previous 5 =
Sites | Previous | Next=
| Next 5 Site=
s | Random Site=
| List Sites<=
/span> ]
&n=
bsp;
14 September 2006 =
------=_NextPart_01C6D8DA.D64E3E80
Content-Location: file:///C:/6A435E52/refractor_bestanden/image001.jpg
Content-Transfer-Encoding: base64
Content-Type: image/jpeg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